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Cancers
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Towards Precision Medicine: From Biomarker Discovery to Novel Therapeutic Target...
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Towards Precision Medicine: From Biomarker Discovery to Novel Therapeutic Target Candidates for Human Cancers

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Biomarkers".

Deadline for manuscript submissions: closed (25 May 2023) | Viewed by 12317

Special Issue Editors

Dr. Silvia Zappavigna

E-Mail Website
Guest Editor
Department of Precision Medicine, University of Campania “L. Vanvitelli”, Via L. De Crecchio 7, 80138 Naples, Italy
Interests: cell death mechanisms; microRNAs; long non coding RNAs; biomarkers; nanotechnology; drug delivery; signal transduction; target therapy; cancer; circulating tumor cells; glioblastoma; prostate cancer; hepatocellular cancer
Special Issues, Collections and Topics in MDPI journals
Dr. Marianna Abate

E-Mail Website
Guest Editor
Department of Precision Medicine, University of Campania Luigi Vanvitelli, Naples, Italy
Interests: oncology; biochemistry; nanotechnologies; RNA interference
Special Issues, Collections and Topics in MDPI journals
Dr. Marco Bocchetti

E-Mail Website
Guest Editor
Department of Precision Medicine, University of Campania “L. Vanvitelli” via L. De Crecchio 7, 80138 Naples, Italy
Interests: microRNAs; long non-coding RNAs; regulation of gene expression; cell signaling; target therapy; laryngeal cancer; hepatocarcinoma; mithocondrial metabolism; biomarkers

Special Issue Information

Dear Colleagues,

The discovery and development of novel biomarkers and therapeutic targets have greatly accelerated progress towards precision medicine in oncology. Multi-platforms for molecular characterization of tumors have given rise to new efforts in performing pathological, biochemical, molecular, and immunological research to study the mechanisms underlying carcinogenesis, with the final aim of finding the cancer biomarkers and molecular targets, which could be applied in clinical practice. Cancer biomarkers are of great interest for early diagnosis, prognosis, and prediction of treatment response and may aid in the development of new anti-cancer targeted therapies with proven benefits for treatment response and survival. However, plenty of research opportunity exists for discovering, developing, and validating cancer biomarkers and targets for improving the clinical outcomes of patients with malignant diseases. The present Special Issue aims to collect the most relevant research in the emerging areas of clinical molecular diagnostics, drug development, and targeting different signaling pathways involved in tumorigenesis.

Dr. Silvia Zappavigna
Dr. Marianna Abate
Dr. Marco Bocchetti
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cancer biomarker
  • predictive biomarker
  • prognosis
  • diagnosis
  • molecular target
  • noncoding RNAs
  • extracellular vesicles
  • circulating tumor cells
  • omic sciences
  • drug design
  • nanodrugs

Published Papers (7 papers)

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Research

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13 pages, 1563 KiB  
Article
A Potential Biomarker of Dynamic Change in Peripheral CD45RA−CD27+CD127+ Central Memory T Cells for Anti-PD-1 Therapy in Patients with Esophageal Squamous Cell Carcinoma
by Mei Sakuma, Kosaku Mimura, Shotaro Nakajima, Akinao Kaneta, Tomohiro Kikuchi, Azuma Nirei, Takeshi Tada, Hiroyuki Hanayama, Hirokazu Okayama, Wataru Sakamoto, Motonobu Saito, Tomoyuki Momma, Zenichiro Saze and Koji Kono
Cancers 2023, 15(14), 3641; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15143641 - 16 Jul 2023
Cited by 2 | Viewed by 1055
Abstract
In order to develop a biomarker predicting the efficacy of treatments for patients with esophageal squamous cell carcinoma (ESCC), we evaluated the subpopulation of T cells in ESCC patients treated with chemotherapy (CT), chemoradiotherapy (CRT), and nivolumab therapy (NT). Fifty-five ESCC patients were [...] Read more.
In order to develop a biomarker predicting the efficacy of treatments for patients with esophageal squamous cell carcinoma (ESCC), we evaluated the subpopulation of T cells in ESCC patients treated with chemotherapy (CT), chemoradiotherapy (CRT), and nivolumab therapy (NT). Fifty-five ESCC patients were enrolled in this study, and peripheral blood samples were collected before and after CT or CRT and during NT. Frequencies of memory, differentiated, and exhausted T cells were evaluated using flow cytometry among cStages, treatment strategies, pathological responses of CT/CRT, and during NT. The frequencies of PD-1+ or TIM-3+CD4+ T cells were significantly higher in patients with cStage IV. PD-1+CD4+ and TIM-3+CD8+ T-cell populations were significantly higher in patients treated with CRT but were not associated with treatment response. The frequencies of both CD4+ and CD8+ CD45RA−CD27+CD127+ central memory T cells (TCM) were significantly decreased during the course of NT in the progressive disease group. Taken together, the alteration in frequency of CD45RA−CD27+CD127+ TCM during NT may be a biomarker to predict its therapeutic response in ESCC patients. Full article
(This article belongs to the Special Issue Towards Precision Medicine: From Biomarker Discovery to Novel Therapeutic Target Candidates for Human Cancers)
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23 pages, 11609 KiB  
Article
Multi-Omics Analysis of GNL3L Expression, Prognosis, and Immune Value in Pan-Cancer
by Pei Liu, Wenjia Guo, Ying Su, Chen Chen, Yuhua Ma, Ping Ma, Cheng Chen and Xiaoyi Lv
Cancers 2022, 14(19), 4595; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14194595 - 22 Sep 2022
Cited by 1 | Viewed by 1759
Abstract
Guanine nucleotide-binding protein-like 3-like protein (GNL3L) is a novel, evolutionarily conserved, GTP-binding nucleolar protein. This study aimed to investigate the expression, prognosis, and immune value of GNL3L in pan-cancer from multiple omics analyses. Firstly, the expression and prognostic value of GNL3L in pan-cancer [...] Read more.
Guanine nucleotide-binding protein-like 3-like protein (GNL3L) is a novel, evolutionarily conserved, GTP-binding nucleolar protein. This study aimed to investigate the expression, prognosis, and immune value of GNL3L in pan-cancer from multiple omics analyses. Firstly, the expression and prognostic value of GNL3L in pan-cancer were discussed using the TIMER2 database, the GEPIA database, the cBioportal database, COX regression analysis, and enrichment analysis. The association of GNL3L with tumor mutational burden (TMB), tumor microsatellite instability (MSI), mismatch repair (MMR) genes, and immune cells was then analyzed. Finally, an esophageal cancer (ESCA) prediction model was established, and GNL3L clone formation assays were performed. The final results showed that GNL3L is differentially expressed in the vast majority of cancers, is associated with the prognosis of various cancers, and may affect cancer occurrence through processes such as ribonucleoprotein, ribosomal RNA processing, and cell proliferation. At the same time, it was found that the correlation between GNL3L and TMB, MSI, MMR, and various immune cells is significant. The established ESCA prediction model had a strong predictive ability, and GNL3L could significantly affect the proliferation of esophageal cancer cells. In conclusion, GNL3L may serve as an important prognostic biomarker and play an immunomodulatory role in tumors. Full article
(This article belongs to the Special Issue Towards Precision Medicine: From Biomarker Discovery to Novel Therapeutic Target Candidates for Human Cancers)
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23 pages, 3433 KiB  
Article
Single B Cell Gene Co-Expression Networks Implicated in Prognosis, Proliferation, and Therapeutic Responses in Non-Small Cell Lung Cancer Bulk Tumors
by Qing Ye and Nancy Lan Guo
Cancers 2022, 14(13), 3123; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14133123 - 25 Jun 2022
Cited by 6 | Viewed by 2329
Abstract
In NSCLC, there is a pressing need for immunotherapy predictive biomarkers. The processes underlying B-cell dysfunction, as well as their prognostic importance in NSCLC, are unknown. Tumor-specific B-cell gene co-expression networks were constructed by comparing the Boolean implication modeling of single-cell RNA sequencing [...] Read more.
In NSCLC, there is a pressing need for immunotherapy predictive biomarkers. The processes underlying B-cell dysfunction, as well as their prognostic importance in NSCLC, are unknown. Tumor-specific B-cell gene co-expression networks were constructed by comparing the Boolean implication modeling of single-cell RNA sequencing of NSCLC tumor B cells and normal B cells. Proliferation genes were selected from the networks using in vitro CRISPR-Cas9/RNA interfering (RNAi) screening data in more than 92 human NSCLC epithelial cell lines. The prognostic and predictive evaluation was performed using public NSCLC transcriptome and proteome profiles. A B cell proliferation and prognostic gene co-expression network was present only in normal lung B cells and missing in NSCLC tumor B cells. A nine-gene signature was identified from this B cell network that provided accurate prognostic stratification using bulk NSCLC tumor transcriptome (n = 1313) and proteome profiles (n = 103). Multiple genes (HLA-DRA, HLA-DRB1, OAS1, and CD74) differentially expressed in NSCLC B cells, peripheral blood lymphocytes, and tumor T cells had concordant prognostic indications at the mRNA and protein expression levels. The selected genes were associated with drug sensitivity/resistance to 10 commonly used NSCLC therapeutic regimens. Lestaurtinib was discovered as a potential repositioning drug for treating NSCLC. Full article
(This article belongs to the Special Issue Towards Precision Medicine: From Biomarker Discovery to Novel Therapeutic Target Candidates for Human Cancers)
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Review

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24 pages, 1646 KiB  
Review
Molecular Classifiers in Skin Cancers: Challenges and Promises
by Ali Azimi and Pablo Fernandez-Peñas
Cancers 2023, 15(18), 4463; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15184463 - 07 Sep 2023
Viewed by 1231
Abstract
Skin cancers are common and heterogenous malignancies affecting up to two in three Australians before age 70. Despite recent developments in diagnosis and therapeutic strategies, the mortality rate and costs associated with managing patients with skin cancers remain high. The lack of well-defined [...] Read more.
Skin cancers are common and heterogenous malignancies affecting up to two in three Australians before age 70. Despite recent developments in diagnosis and therapeutic strategies, the mortality rate and costs associated with managing patients with skin cancers remain high. The lack of well-defined clinical and histopathological features makes their diagnosis and classification difficult in some cases and the prognostication difficult in most skin cancers. Recent advancements in large-scale “omics” studies, including genomics, transcriptomics, proteomics, metabolomics and imaging-omics, have provided invaluable information about the molecular and visual landscape of skin cancers. On many occasions, it has refined tumor classification and has improved prognostication and therapeutic stratification, leading to improved patient outcomes. Therefore, this paper reviews the recent advancements in omics approaches and appraises their limitations and potential for better classification and stratification of skin cancers. Full article
(This article belongs to the Special Issue Towards Precision Medicine: From Biomarker Discovery to Novel Therapeutic Target Candidates for Human Cancers)
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25 pages, 2669 KiB  
Review
Patient-Derived Ex Vivo Cultures and Endpoint Assays with Surrogate Biomarkers in Functional Testing for Prediction of Therapeutic Response
by Yoshiyuki Tsukamoto, Yuka Hirashita, Tomotaka Shibata, Shoichi Fumoto, Shusaku Kurogi, Chisato Nakada, Keisuke Kinoshita, Takafumi Fuchino, Kazunari Murakami, Masafumi Inomata, Masatsugu Moriyama and Naoki Hijiya
Cancers 2023, 15(16), 4104; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15164104 - 15 Aug 2023
Viewed by 1494
Abstract
Prediction of therapeutic outcomes is important for cancer patients in order to reduce side effects and improve the efficacy of anti-cancer drugs. Currently, the most widely accepted method for predicting the efficacy of anti-cancer drugs is gene panel testing based on next-generation sequencing. [...] Read more.
Prediction of therapeutic outcomes is important for cancer patients in order to reduce side effects and improve the efficacy of anti-cancer drugs. Currently, the most widely accepted method for predicting the efficacy of anti-cancer drugs is gene panel testing based on next-generation sequencing. However, gene panel testing has several limitations. For example, only 10% of cancer patients are estimated to have druggable mutations, even if whole-exome sequencing is applied. Additionally, even if optimal drugs are selected, a significant proportion of patients derive no benefit from the indicated drug treatment. Furthermore, most of the anti-cancer drugs selected by gene panel testing are molecularly targeted drugs, and the efficacies of cytotoxic drugs remain difficult to predict. Apart from gene panel testing, attempts to predict chemotherapeutic efficacy using ex vivo cultures from cancer patients have been increasing. Several groups have retrospectively demonstrated correlations between ex vivo drug sensitivity and clinical outcome. For ex vivo culture, surgically resected tumor tissue is the most abundant source. However, patients with recurrent or metastatic tumors do not usually undergo surgery, and chemotherapy may be the only option for those with inoperable tumors. Therefore, predictive methods using small amounts of cancer tissue from diagnostic materials such as endoscopic, fine-needle aspirates, needle cores and liquid biopsies are needed. To achieve this, various types of ex vivo culture and endpoint assays using effective surrogate biomarkers of drug sensitivity have recently been developed. Here, we review the variety of ex vivo cultures and endpoint assays currently available. Full article
(This article belongs to the Special Issue Towards Precision Medicine: From Biomarker Discovery to Novel Therapeutic Target Candidates for Human Cancers)
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19 pages, 2110 KiB  
Review
Targeting JWA for Cancer Therapy: Functions, Mechanisms and Drug Discovery
by Kun Ding, Xia Liu, Luman Wang, Lu Zou, Xuqian Jiang, Aiping Li and Jianwei Zhou
Cancers 2022, 14(19), 4655; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14194655 - 24 Sep 2022
Cited by 5 | Viewed by 1866
Abstract
Tumor heterogeneity limits the precision treatment of targeted drugs. It is important to find new tumor targets. JWA, also known as ADP ribosylation factor-like GTPase 6 interacting protein 5 (ARL6IP5, GenBank: AF070523, 1998), is a microtubule-associated protein and an environmental response gene. Substantial [...] Read more.
Tumor heterogeneity limits the precision treatment of targeted drugs. It is important to find new tumor targets. JWA, also known as ADP ribosylation factor-like GTPase 6 interacting protein 5 (ARL6IP5, GenBank: AF070523, 1998), is a microtubule-associated protein and an environmental response gene. Substantial evidence shows that JWA is low expressed in a variety of malignancies and is correlated with overall survival. As a tumor suppressor, JWA inhibits tumor progression by suppressing multiple oncogenes or activating tumor suppressor genes. Low levels of JWA expression in tumors have been reported to be associated with multiple aspects of cancer progression, including angiogenesis, proliferation, apoptosis, metastasis, and chemotherapy resistance. In this review, we will discuss the structure and biological functions of JWA in tumors, examine the potential therapeutic strategies for targeting JWA and explore the directions for future investigation. Full article
(This article belongs to the Special Issue Towards Precision Medicine: From Biomarker Discovery to Novel Therapeutic Target Candidates for Human Cancers)
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Other

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4 pages, 519 KiB  
Perspective
A New Source of Heterogeneity in Comparative and Translational Clinical Trials: The “Border-Time” Bias
by Mariachiara Santorsola, Michele Caraglia, Guglielmo Nasti and Alessandro Ottaiano
Cancers 2022, 14(21), 5265; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14215265 - 26 Oct 2022
Viewed by 925
Abstract
The use of target-oriented drugs is profoundly changing the anti-cancer treatments. This new and expanding therapeutic context relies on the translation of biomarkers expression (laboratory testing) into clinical practice (treatment). Progression-free survival is a primary or co-primary endpoint in the large part of [...] Read more.
The use of target-oriented drugs is profoundly changing the anti-cancer treatments. This new and expanding therapeutic context relies on the translation of biomarkers expression (laboratory testing) into clinical practice (treatment). Progression-free survival is a primary or co-primary endpoint in the large part of comparative clinical trials about biologic anti-cancer agents. Here, we describe the “border time” bias represented by specific time points and intervals that are an underestimated source of methodologic heterogeneity and can contribute to wrong evaluation of time-to-outcome. These issues are concentrated at the beginning (head: pre-screening and screening activities) and at the end (tail: modalities of disease reassessment) of the anti-cancer treatment and can represent a time-related bias. Reporting, and ideally shortening, the time spent in pre-screening and screening activities with synthetic and innovative methodological tools as well as more harmonized rules about timing of disease reassessment can contribute to reduce, or even prevent, this bias in clinical studies. Full article
(This article belongs to the Special Issue Towards Precision Medicine: From Biomarker Discovery to Novel Therapeutic Target Candidates for Human Cancers)
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